DeepSeek/FlashMLA
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cuda12.8 recommendation

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2025-02-26 00:05:57 +08:00
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@@ -20,7 +20,7 @@ python setup.py install
python tests/test_flash_mla.py
```
Achieving up to 3000 GB/s in memory-bound configuration and 580 TFLOPS in computation-bound configuration on H800 SXM5, using CUDA 12.6.
Achieving up to 3000 GB/s in memory-bound configuration and 580 TFLOPS in computation-bound configuration on H800 SXM5, using CUDA 12.8.
### Usage
@@ -42,6 +42,7 @@ for i in range(num_layers):
- Hopper GPUs
- CUDA 12.3 and above
- **But we highly recommend 12.8 or above for the best performance**
- PyTorch 2.0 and above
## Acknowledgement
@@ -52,7 +53,7 @@ FlashMLA is inspired by [FlashAttention 2&3](https://github.com/dao-AILab/flash-
```bibtex
@misc{flashmla2025,
title={FlashMLA: Efficient MLA decoding kernel},
title={FlashMLA: Efficient MLA decoding kernels},
author={Jiashi Li},
year={2025},
publisher = {GitHub},